Transcriptome and proteome of human hepatocellular carcinoma reveal shared metastatic pathways with significant genes

Previously isolated pathways screened from individual genes were investigated at either the transcriptional or translational level; however, the consistency between the pathways screened at the gene expression levels was obscure in metastatic human hepatocellular carcinoma (HCC). To elucidate this question, we performed a transcriptomic (16,353 genes) and proteomic (7861 proteins) analysis simultaneously on six metastatic HCC cell lines against two nonmetastatic HCC cell lines, with all HBV traceable and close genetic-backgrounds for a comparative study. The quantitative and integrated results showed that significant genes were screened differentially with 351 transcripts from the transcriptome and 304 proteins from the proteome, with limited overlapping genes (7%). However, we discovered that these discrete 351 transcripts and 304 proteins screened share extrusive significant-pathways/networks with a 77% overlap, including active TGF-β, RAS, NFκB, and Wnt, and inactive HNF4A, which are responsible for HCC metastasis. We conclude that the discrete, but significant genes predicted by either ome play intrinsically important roles in the linkage of responsible pathways shared by both omes in HCC metastasis.

A more powerful test based on ratio distribution for retention noninferiority hypothesis

Rothmann et al. ( 2003 ) proposed a method for the statistical inference of fraction retention noninferiority (NI) hypothesis. A fraction retention hypothesis is defined as a ratio of the new treatment effect verse the control effect in the context of a time to event endpoint. One of the major concerns using this method in the design of an NI trial is that with a limited sample size, the power of the study is usually very low. This makes an NI trial not applicable particularly when using time to event endpoint. To improve power, Wang et al. ( 2006 ) proposed a ratio test based on asymptotic normality theory. Under a strong assumption (equal variance of the NI test statistic under null and alternative hypotheses), the sample size using Wang's test was much smaller than that using Rothmann's test. However, in practice, the assumption of equal variance is generally questionable for an NI trial design. This assumption is removed in the ratio test proposed in this article, which is derived directly from a Cauchy-like ratio distribution. In addition, using this method, the fundamental assumption used in Rothmann's test, that the observed control effect is always positive, that is, the observed hazard ratio for placebo over the control is greater than 1, is no longer necessary. Without assuming equal variance under null and alternative hypotheses, the sample size required for an NI trial can be significantly reduced if using the proposed ratio test for a fraction retention NI hypothesis.